The Space Robotics Challenge (SRC) came to a close last week with a wonderful celebration event at Space Center Houston. The celebration event brought together competitors and organizers over two days with tours of Johnson Space Center (JSC), team presentations, and an award ceremony.

The SRC tasked teams with developing and displaying the ability of the Valkyrie (R5) robot to assist in a virtual NASA Mars mission. A prize pool of $1 million was available to successful teams. The following scenario served as a backdrop for the challenge.

In the not too distant future, Valkyrie has arrived on Mars along with supplies ahead of a human mission. Overnight a dust storm damaged the habitat and solar array, and caused the primary communication antenna to become misaligned. Valkyrie must now repair an air leak in the habitat, deploy a new solar panel, and align the communication antenna.


Teams developed software to control Valkyrie in order to resolve the problems caused by the dust storm. Gazebo was used as the simulation platform, with integration to a walking controller from Florida Institute for Human and Machine Cognition (IHMC). Additional ROS interfaces were provided by JSC.

Each team was evaluated according to a scoring metric that considered the number of tasks completed and the time required to complete the tasks. Unique to SRC was a focus on completing multiple tasks sequentially, without falling. The winning teams were able to complete numerous tasks, even in the presence of significant network latency and bandwidth restrictions.

The top four teams are:

First place: Coordinated Robotics

Coordinated Robotics is a one-man team from California that has previously competed in other robotics challenges. Because dexterous control of a robot requires coordination between sensors and actuators, the team name of Coordinated Robotics was formulated. Hoping to win prizes and learn more about humanoids, Coordinated Robotics will focus on manipulation of humanoids to excel in the competition.

Second place: Walk Softly

Team Walk Softly joins the fray from upstate New York. The team name is reminiscent of a phrase often attributed to former President Theodore Roosevelt, "speak softly and carry a big stick - you will go far." Team members are coworkers at GE Global Research who have an interest in humanoid robots and decided to enter on their own time. The team is excited to see the innovative solutions that come out of this challenge.

Third place: Olympus Mons

Ten robotics and software specialists representing six countries make up Team Olympus Mons. Olympus Mons is the name of the largest discovered volcano in the solar system and is located on Mars, where the simulated competition will take place; this is where they gained inspiration for their team name. The team members are all current or former employees at PAL Robotics who have stayed in touch throughout the years. Although they are not eligible for prize money, Team Olympus Mons entered the competition to have fun and become more involved in simulated space exploration.

Fourth place: ZARJ

ZARJ is represented by four engineers and programmers based in Minnesota. The Team has been interested in NASA's Centennial Challenges for the past four years, but did not have the time or resources to enter the contests. Finally, ZARJ was able to enter the Space Robotics Challenge before the deadline arrived. If ZARJ is awarded prize money, they plan to distribute it equally between team members to defray some competition travel costs.

Congratulations to all teams that participated in the competition!

Reposted from the OSRF Blog.

We are happy to announce the final results of the Agile Robotics for Industrial Automation Competition (ARIAC).

ARIAC is a simulation-based competition designed to promote agility in industrial robot systems by utilizing the latest advances in artificial intelligence and robot planning. The goal is to enable industrial robots on the shop floors to be more productive, more autonomous, and more responsive to the needs of shop floor workers. The virtual nature of the competition enabled participation of teams affiliated with companies and research institutions from across three continents.

While autonomously completing pick-and-place kit assembly tasks, teams were presented with various agility challenges developed based on input from industry representatives. These challenges include failing suction grippers, notification of faulty parts, and reception of high-priority orders that would prompt teams to decide whether or not to reuse existing in-progress kits.

Teams had control over their system’s suite of sensors positioned throughout the workcell, made up of laser scanners, intelligent vision sensors, quality control sensors and interruptible photoelectric break-beams. Each team participating in the finals chose a unique sensor configuration with varying associated costs and impact on the team’s strategy.

The diversity in the teams’ strategies and the impact of their sensor configurations can be seen in the video of highlights from the finals:

Scoring was performed based on a combination of performance, efficiency and cost metrics over 15 trials. The overall standings of the top teams are as follows.

First place: Realization of Robotics Systems, Center for Advanced Manufacturing, University of Southern California

Second place: FIGMENT, Pernambuco Federal Institute of Education, Science, and Technology / Federal University of Pernambuco

Third place: TeamCase, Case Western Reserve University

Top-performing teams will be presenting at IROS 2017 in Vancouver, Canada in a workshop held on Sunday, September 24th. Details for interested parties are available at

The IROS workshop is open to all, even those that did not compete. In addition to having presentations about approaches used in the competition, we will also be exploring plans for future competitions. If you would like to give a presentation about agility challenges you would like to see in future competitions, please contact Craig Schlenoff (

Congratulations to all teams that participated in the competition. We look forward to seeing you in Vancouver!

Vehicle simulation


Reposted from the OSRF Blog.

We are excited to show off a simulation of a Prius in Mcity using ROS Kinetic and Gazebo 8. ROS enabled the simulation to be developed faster by using existing software and libraries. The vehicle's throttle, brake, steering, and transmission are controlled by publishing to a ROS topic. All sensor data is published using ROS, and can be visualized with RViz.

We leveraged Gazebo's capabilities to incorporate existing models and sensors. The world contains a new model of Mcity and a freeway interchange. There are also models from the gazebo models repository including dumpsters, traffic cones, and a gas station. On the vehicle itself there is a 16 beam lidar on the roof, 8 ultrasonic sensors, 4 cameras, and 2 planar lidar.

The simulation is open source and available at on GitHub at osrf/car_demo. Try it out by installing nvidia-docker and pulling "osrf/car_demo" from Docker Hub. More information about building and running is available in the README in the source repository.

Download (8.0.0)

Changelog | Migration Guide | Roadmap

End-of-life Notice

Gazebo 6.x and 5.x have reached the end of their lives. We will continue to answer questions about these versions, but we will stop fixing bugs.

Highlights for 8.0.0

  • Plotting Utility
  • Video Recording
  • QT5 support
  • Visual markers
  • Improved quadcopter simulation
  • Import OBJ files
  • Generalization of Actor animations
  • Migration to Ignition-math

We are proud to announce the release of Gazebo 8. This version of Gazebo has short term support with an end-of-life on January 15, 2019.

A major API change comes with Gazebo8. This API change centers around the transition from Gazebo's internal math library to Ignition Math. Please refer to the changelog and migration guide to help your transition.

The ability to dynamically and programmatically add visual elements to Gazebo has been added through a visual marker interface. Visual markers can consist of simple shapes, lines, triangles, and text. Additional features associated with visual markers can be found through the gz marker -h command line tool. A C++ example demonstrates how to manipulate visual markers from a stand-alone application.

We continually strive to improve Gazebo's user experience and offer features that benefit a wide audience. To this end, a feature rich plotting utility has been integrated with Gazebo. This utility supports plotting data from topics, models, and simulation parameters. Multiple plots can be created, and data can be exported to CSV or PDF files. Try inserting a model, such as the Double Pendulum, and press ctrl-p.

Following the same rationale as the plotting utility, we are pleased to announce the integration of video recording in Gazebo 8. Simply select the camera icon on the right hand side of the tool bar to start recording into an MP4, AVI, or OGV file. Select the icon again to stop recording and save the video file.

Enjoy the new release, and thanks for all the contributions,

  OSRF Development Team

Gazebo Newsletter 7 November 2016

The Space Robotics Challenge (SRC), a NASA Centennial Challenge, has recently kicked off. The SRC "tasks teams with developing and displaying the ability of an R5 robot to assist in the procedures of a NASA mission, such as one to Mars, offering a $1 million prize pool for successful teams."

The SRC uses Gazebo and a set of plugins to simulate R5 and the challenge environments. Qualifications are underway, where competitors solve two tasks on their personal computers. Finals will take place next year, and will utilize CloudSim with Gazebo.


  • Ignition Msgs 0.6.0
  • Ignition Math 2.6.0

Tip of the month

Gazebo can generate a lot of data, especially when simulating complex robots. This data can be used to tune model parameters, debug unexpected behavior, write unit tests, and peform system introspection and identification. However, raw data is difficult for a human to consume.

Gazebo 8 will ship with a plotting utility that can display in real time data produced by Gazebo. The plotting utility is capable of processing data from simulation models and data available on topics. Below is an example image of the plotting utility.


Featured Model

A generic Mars rover is available in the model database. rover


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